![Logo](https://github.com/Atif-Anwer/SpecSeg/raw/main/SpecSeg_logo.png)
Official repository for the article @ MDPI Sensors »
@Article{s22176552,
AUTHOR = {Anwer, Atif and Ainouz, Samia and Saad, Mohamad Naufal Mohamad and Ali, Syed Saad Azhar and Meriaudeau, Fabrice},
TITLE = {SpecSeg Network for Specular Highlight Detection and Segmentation in Real-World Images},
JOURNAL = {Sensors},
VOLUME = {22},
YEAR = {2022},
NUMBER = {17},
ARTICLE-NUMBER = {6552},
URL = {https://www.mdpi.com/1424-8220/22/17/6552},
ISSN = {1424-8220},
DOI = {10.3390/s22176552}
}
The Article PDF is open access and can be downloaded directly from MDPI.
There is now a Live Demo of the SpecSeg network on Huggingface. Please feel free to test at Huggingface SpecSeg space. (Note: Doesnt look correct on Safari browser due to Huggingface rendering, use Firefox/Chromimum based browsers please).
This repository is the implementation of our paper 'SpecSeg Network for Specular Highlight Detection and Segmentation in Real-World Images'. The developed network and pretrained weights can be used for network training and testing. Please cite the paper if you use them and find them useful.
Full article @ MDPI Sensors
- Tested with Python 3.7, Tensorflow 2.5+ on local GPU (CUDA 11.3)
- Tested with Python 3.7, Tensorflow 2.8+ on Google Colab
- Uses the Segmentation Models library
The datasets used in the paper can be found at the following Github Repos (property of the respective authors):
- PSD Dataset, Wu et al.
- SIHQ Dataset, Fu et al.
For training on your dataset, please change the path to the dataset root folder in the Jupyter notebook or python script.
- Jupyter Notebook (for Colab)
- Pretrained weights
- Python Script
Distributed under the GNU General Public License v3.0 License, for research training and/or testing purposes. Pleas cite our paper if you use this code or network. For more details, please see Choose a license and the Liscence.txt file.